Review



routine for impulsed fitting  (MathWorks Inc)


Bioz Verified Symbol MathWorks Inc is a verified supplier  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    MathWorks Inc routine for impulsed fitting
    Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from <t>IMPULSED</t> and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.
    Routine For Impulsed Fitting, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/routine+for+impulsed+fitting/pmc12127095-93-4-1
    Average 90 stars, based on 1 article reviews
    routine for impulsed fitting - by Bioz Stars, 2026-10
    90/100 stars

    Images

    1) Product Images from "Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time‐Dependent Diffusion MRI"

    Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time‐Dependent Diffusion MRI

    Journal: Cancer Science

    doi: 10.1111/cas.70036

    Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from IMPULSED and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.
    Figure Legend Snippet: Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from IMPULSED and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.

    Techniques Used: Diffusion-based Assay, Staining, Histopathology

    Related Articles

    Diffusion-based Assay:

    Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time‐Dependent Diffusion MRI
    Article Snippet: The MATLAB routine for IMPULSED fitting is provided at https://github.com/wjgxw/ogse .

    Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time-Dependent Diffusion MRI.
    Article Snippet: The MATLAB routine for IMPULSED fitting is provided at https:// github. com/ wjgxw/ ogse.

    Staining:

    Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time‐Dependent Diffusion MRI
    Article Snippet: The MATLAB routine for IMPULSED fitting is provided at https://github.com/wjgxw/ogse .

    Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time-Dependent Diffusion MRI.
    Article Snippet: The MATLAB routine for IMPULSED fitting is provided at https:// github. com/ wjgxw/ ogse.

    Histopathology:

    Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time‐Dependent Diffusion MRI
    Article Snippet: The MATLAB routine for IMPULSED fitting is provided at https://github.com/wjgxw/ogse .

    Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time-Dependent Diffusion MRI.
    Article Snippet: The MATLAB routine for IMPULSED fitting is provided at https:// github. com/ wjgxw/ ogse.



    Similar Products

    routine for impulsed fitting  (MathWorks Inc)
    90
    MathWorks Inc routine for impulsed fitting
    Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from <t>IMPULSED</t> and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.
    Routine For Impulsed Fitting, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/routine+for+impulsed+fitting/pmc12127095-93-4-1
    Average 90 stars, based on 1 article reviews
    routine for impulsed fitting - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from IMPULSED and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.

    Journal: Cancer Science

    Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time‐Dependent Diffusion MRI

    doi: 10.1111/cas.70036

    Figure Lengend Snippet: Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from IMPULSED and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.

    Article Snippet: The MATLAB routine for IMPULSED fitting is provided at https://github.com/wjgxw/ogse .

    Techniques: Diffusion-based Assay, Staining, Histopathology